Why social values cannot be changed for the sake of conservation

The hope for creating widespread change in social values has endured among conservation professionals since early calls by Aldo Leopold for a “land ethic.” However, there has been little serious attention in conservation to the fields of investigation that address values, how they are formed, and how they change. We introduce a social–ecological systems conceptual approach in which values are seen not only as motivational goals people hold but also as ideas that are deeply embedded in society's material culture, collective behaviors, traditions, and institutions. Values define and bind groups, organizations, and societies; serve an adaptive role; and are typically stable across generations. When abrupt value changes occur, they are in response to substantial alterations in the social–ecological context. Such changes build on prior value structures and do not result in complete replacement. Given this understanding of values, we conclude that deliberate efforts to orchestrate value shifts for conservation are unlikely to be effective. Instead, there is an urgent need for research on values with a multilevel and dynamic view that can inform innovative conservation strategies for working within existing value structures. New directions facilitated by a systems approach will enhance understanding of the role values play in shaping conservation challenges and improve management of the human component of conservation.     

Performance of IUCN proxies for generation length

One of the criteria used by the International Union for Conservation of Nature (IUCN) to assess threat status is the rate of decline in abundance over 3 generations or 10 years, whichever is longer. The traditional method for calculating generation length (T) uses age‐specific survival and fecundity, but these data are rarely available. Consequently, proxies that require less information are often used, which introduces potential biases. The IUCN recommends 2 proxies based on adult mortality rate, = α + 1/d, and reproductive life span, = α + z^*RL, where α is age at first reproduction, d is adult mortality rate, RL is reproductive life span, and z is a coefficient derived from data for comparable species. We used published life tables for 78 animal and plant populations to evaluate precision and bias of these proxies by comparing and with true generation length. Mean error rates in estimating T were 31% for and 20% for , but error rates for were 16% when we subtracted 1 year ( ), as suggested by theory; also provided largely unbiased estimates regardless of the true generation length. Performance of depends on compilation of detailed data for comparable species, but our results suggest taxonomy is not a reliable indicator of comparability. All 3 proxies depend heavily on a reliable estimate of age at first reproduction, as we illustrated with 2 test species. The relatively large mean errors for all proxies emphasized the importance of collecting the detailed life‐history information necessary to calculate true generation length. Unfortunately, publication of such data is less common than it was decades ago. We identified generic patterns of age‐specific change in vital rates that can be used to predict expected patterns of bias from applying .     

How to Constrain Multi‐Objective Calibrations of the SWAT Model Using Water Balance Components

Accurate discharge simulation is one of the most common objectives of hydrological modeling studies. However, a good simulation of discharge is not necessarily the result of a realistic simulation of hydrological processes within the catchment. We propose an evaluation framework that considers both discharge and water balance components as evaluation criteria for calibration of the Soil and Water Assessment Tool (SWAT). In this study, we integrated average annual values of surface runoff, groundwater flow, and evapotranspiration in the model evaluation procedure to constrain the selection of good model runs for the Little River Experimental Watershed in Georgia, United States. For evaluating water balance and discharge dynamics, the Nash‐Sutcliffe efficiency (NSE) and percent bias (PBIAS) were used. In addition, the ratio of root mean square error and standard deviation of measured data (RSR) was calculated for individual segments of the flow duration curve to identify the best model runs in terms of discharge magnitude. Our results indicate that good statistics for discharge do not guarantee realistic simulations of individual water balance components. Therefore, we recommend constraining the ranges of water balance components to achieve a more realistic simulation of the entire hydrological system, even if tradeoffs between good statistics for discharge simulations and reasonable amounts of the water balance components are unavoidable. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

A Comprehensive Python Toolkit for Accessing High‐Throughput Computing to Support Large Hydrologic Modeling Tasks

The National Flood Interoperability Experiment (NFIE) was an undertaking that initiated a transformation in national hydrologic forecasting by providing streamflow forecasts at high spatial resolution over the whole country. This type of large‐scale, high‐resolution hydrologic modeling requires flexible and scalable tools to handle the resulting computational loads. While high‐throughput computing (HTC) and cloud computing provide an ideal resource for large‐scale modeling because they are cost‐effective and highly scalable, nevertheless, using these tools requires specialized training that is not always common for hydrologists and engineers. In an effort to facilitate the use of HTC resources the National Science Foundation (NSF) funded project, CI‐WATER, has developed a set of Python tools that can automate the tasks of provisioning and configuring an HTC environment in the cloud, and creating and submitting jobs to that environment. These tools are packaged into two Python libraries: CondorPy and TethysCluster. Together these libraries provide a comprehensive toolkit for accessing HTC to support hydrologic modeling. Two use cases are described to demonstrate the use of the toolkit, including a web app that was used to support the NFIE national‐scale modeling.     

Does the Temporal Resolution of Precipitation Input Influence the Simulated Hydrological Components Employing the SWAT Model?

This study aimed to evaluate the influence of sub‐daily precipitation time steps on model performance and hydrological components by applying the Green and Ampt infiltration method using the Soil and Water Assessment Tool (SWAT). Precipitation was measured at a resolution of 0.1 mm and aggregated to 5‐, 15‐, 30‐, and 60‐min time steps. Daily discharge data over a 10‐year period were used to calibrate and validate the model. Following a global sensitivity analysis, relevant parameters were optimized through an automatic calibration procedure using SWAT‐CUP for each time step. Daily performance statistics were almost equal among all four time steps (NSE ≈ 0.47). Discharge mainly consisted of groundwater flow (55%) and tile flow (42%), in reasonable proportions for the investigated catchment. In conclusion, model outputs were almost identical, showing simulations responded nearly independently of the chosen precipitation time step. This held true for (1) the selection of sensitive parameters, (2) performance statistics, (3) the shape of the hydrographs, and (4) flow components. However, a scenario analysis revealed that the precipitation time step becomes important when saturated hydraulic conductivities are low and curve numbers are high. The study suggests that there is no need in using precipitation time steps <1 h for lowland catchments dominated by soils with a low surface runoff potential if daily flow values are being considered. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Evaluation of Existing and Modified Wetland Equations in the SWAT Model

The ability to accurately simulate flow and nutrient removal in treatment wetlands within an agricultural, watershed‐scale model is needed to develop effective plans for meeting nutrient reduction goals associated with protection of drinking water supplies and reduction of the Gulf of Mexico hypoxic zone. The objectives of this study were to incorporate new equations for wetland hydrology and nutrient removal in Soil and Water Assessment Tool (SWAT), compare model performance using original and improved equations, and evaluate the ramifications of errors in watershed and tile drain simulation on prediction of NO₃‐N dynamics in wetlands. The modified equations produced Nash‐Sutcliffe Efficiency values of 0.88 to 0.99 for daily NO₃‐N load predictions, and percent bias values generally less than 6%. However, statistical improvement over the original equations was marginal and both old and new equations provided accurate simulations. The new equations reduce the model's dependence on detailed monitoring data and hydrologic calibration. Additionally, the modified equations increase SWAT's versatility by incorporating a weir equation and an irreducible nutrient concentration and temperature coefficient. Model improvements enhance the utility of SWAT for simulating flow and nutrients in wetlands and other impoundments, although performance is limited by the accuracy of inflow and NO₃‐N predictions from the contributing watershed. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Multiresidue determination of carbamate,organochlorine, organophosphorus,and dicarboximide pesticides in lettuce by GC/MS

An extraction method based on matrix solid-phase dispersion was developed to determine pirimicarb, methyl parathion, malathion, procymidone, α -endosulfan and β -endosulfan in lettuce using gas chromatography-mass spectrometry. The best results were obtained using 4.0 g of lettuce, 2.0 g of silica as dispersant sorbent, 0.1 g of activated carbon as clean up sorbent and acetonitrile as eluting solvent. The method was validated using lettuce samples fortified with pesticides at six different concentration levels (0.1 to 2.0 mg/kg). Average recoveries (7 replicates) ranged from 50 to 120 %, with relative standard deviations between 0.6 and 8.0 %. Detection and quantification limits for lettuce ranged from 0.01 to 0.02 mg/kg and 0.04 to 0.10 mg/kg, respectively.     

Evaluation and validation of two different chromatographic methods (HPLC and LC-MS/MS) for the determination and confirmation of ochratoxin A in pig tissues

This study was undertaken to compare two different analytical methods for the determination and confirmation of ochratoxin A (OTA) in blood serum, kidney and liver of pigs. Sample clean-up was based on liquid-liquid phase extraction. The detection of OTA was accomplished with high-performance liquid chromatography (HPLC) combined either with fluorescence detection (FL) or electro spray ionization (ESI+) tandem mass spectrometry (MS–MS). Comparative method evaluation was based on the investigation of 90 samples of blood serum, kidney and liver per animal originating from different regions of Serbia. The analytical results are discussed in view of the respective method validation data and the corresponding experimental protocols. In general, analytical data obtained with (LC–MS–MS) liquid chromatography electro spray tandem mass spectro metry detection offered comparable good results at the sub-ppb concentration level. The results indicate that the liquid chromatography electro spray tandem mass spectrometric (LC-MS/MS) method was more specific and sensitive for the analysis and confirmation of ochratoxin A in pig tissues then high pressure liquid chromatography (HPLC) method after methylation of OTA.     

Pesticide dissipation curves in peach,pear and tomato crops in Uruguay*

Dissipation curves of azoxystrobin and of the neonicotinoids acetamiprid and thiacloprid in peach; azinphos-methyl and carbaryl in pear and azoxystrobin, chlorfenapyr and chlorpyrifos in high-tunnel tomato crops were studied in the Southern region of Uruguay. An analytical methodology based on solid phase extraction (SPE) and detection by High Performance Liquid Chromatography with Diode Array Detector (HPLC/DAD) was used for acetamiprid and thiacloprid. Coupled SPE and detection by Gas Chromatography with Mass Selective Detector (GC/MSD) was used for the detection of azinphos-methyl, azoxystrobin, carbaryl, chlorfenapyr and chlorpyrifos residues. Curves were modeled mathematically with Solver program of Microsoft Excel®. The best fit for acetamiprid and thiacloprid in peach was achieved with the exponential model (r²=0.961 and 0.944, respectively). In the case of peach fruits there is not a Maximum Residue Limit (MRL) for acetamiprid in the Codex Alimentarius, while 0.5 mg/kg is the value rated for thiacloprid. The MRLs accepted by the European Union (EU) are 0.1 mg/kg for acetamiprid and 0.3 mg/kg for thiacloprid. According to the curves determined in these experiments, thiacloprid residues 10 to 12 days after application (daa) were below the MRLs established by both sources. In the case of acetamiprid, 25 daa would be required, according to the exponential mathematical model, to get residues levels below the MRL values established by the EU. For azinphos methyl in pear, the residues detected were mathematically fitted to an exponential model (r²=0.999). According to it, residue levels under the MRL established by the EU (0.05 mg/kg) are gotten in our conditions in 20 daa. In plastic tunnel tomato chlorfenapyr residues were not detected from 16 daa, having the dissipation curve an exponential trend. In the same condition, there was not a decay of the azoxystrobin concentration during a 24-day trial, being it around 0.40 ± 0.05 mg/kg.